Data Engineer

About Odyssey Logistics

Odyssey Logistics is a global logistics and supply chain partner helping businesses optimize performance through fully integrated, end-to-end solutions. We connect transportation, technology, and expertise across a broad network of services including 3PL and 4PL managed services, multimodal and intermodal transport, warehousing, trucking, Jones Act Ocean, and customs brokerage, ensuring goods move reliably, efficiently, and intelligently around the world.

Today, Odyssey supports more than 6,000 customers globally, delivering scalable, data driven solutions across complex supply chains. What started with a single client has grown into a dynamic, evolving organization focused on performance, precision, and long term partnership.

What Sets Us Apart:

Our work is complex, fast moving, and highly collaborative. Success here requires people who think strategically, operate with urgency, and navigate across functions to solve real business challenges. We value individuals who take ownership, challenge the status quo, and turn insight into action.

Our culture is grounded in five core values:
Win Together, Innovate Boldly, Drive Results, Customer Centric, and Guide with Care. These are not just principles; they shape how we make decisions, partner with customers, and show up for each other. At Odyssey, you are not just part of a company; you are part of building what comes next.

The Role:

Location:

Charlotte, NC

Hybrid:
Monday-Thursday onsite and Friday Remote

Reports to:

Data Engineering Manager

* All applicants must be currently authorized to work in the United States. No relocation allowance will be considered unless specifically addressed.

Role Summary

We are seeking a Data Engineer to drive Odyssey's enterprise data engineering strategy. This role will build, maintain, and improve scalable data pipelines, analytics-ready data models, and lakehouse solutions that power reporting, self-service analytics, and AI/ML use cases. This role also acts as an analytics consultant to business teams-partnering with stakeholders to translate business questions into data-driven solutions that drive measurable ROI, operational efficiency, and decision impact.

What

You'll Do:
Data Architecture & Engineering

Build and maintain scalable data lake and lakehouse solutions that integrate diverse enterprise data sources into canonical models and curated datasets. Develop and operate batch and streaming pipelines that ensure reliable, performant, and accurate data delivery. Support both batch and near-real-time data processing for operational and analytical use cases.

Development & Code Quality

Write production-quality Python, SQL, and Spark code following engineering best practices. Contribute to CI/CD pipelines, version control workflows, and code reviews to maintain high-quality, secure deployments. Implement data validation, reconciliation, and basic observability to support data reliability and trust.

Data Modeling & Analytics Enablement

Develop analytics-ready data models - facts, dimensions, and metrics - that support self-service BI and reporting. Support Sigma Computing by maintaining semantic layers, datasets, and governed metrics for consistent business reporting. Collaborate with Analytics Engineers to define data transformations, metric logic, and data contracts.

Business Partnership & Consulting

Act as an analytics consultant to business stakeholders by translating operational and strategic questions into scalable data and analytics solutions. Partner with functional teams across Sales, Finance, Operations, and Shared Services to identify high-impact use cases that drive measurable business outcomes. Help stakeholders understand data limitations, assumptions, and opportunities to maximize business value from analytics investments.

Performance, Security & Compliance

Optimize cloud compute and storage usage across Databricks and AWS to support cost efficiency. Apply secure-by-design practices including RBAC, encryption, and approved access controls.

Operations & Support

Troubleshoot pipeline failures, performance issues, and data inconsistencies and implement improvements. Support vendor tools and platforms through integrations, upgrades, and issue resolution. Maintain documentation for data pipelines, data models, and analytics datasets.

What You Bring:

Technical Skills

Strong SQL and query design experience including performance tuning, query optimization, and data validation across heterogeneous data sources. Hands-on proficiency in…